Literature DB >> 25037267

Implicit learning mediates base rate acquisition in perceptual categorization.

Corey J Bohil1, Andrew J Wismer.   

Abstract

We explored the possibility, suggested by Koehler (Behavioral and Brain Sciences, 19, 1-53, 1996; also Spellman Behavioral and Brain Sciences, 19, 38, 1996), that implicit learning mediates the influence of base-rates on category knowledge acquired through direct experience. In two experiments, participants learned simple perceptual categories with unequal base-rates (i.e., presentation frequency). In Experiment 1, participants received either response training or observational training. In Experiment 2, participants received response training with either immediate or delayed feedback. In previous studies, observational training and delayed feedback training have been shown to disrupt implicit learning. We found that base-rate influence was weaker in these conditions when category discriminability was low (i.e., when category membership was difficult to determine). This conclusion was based on signal detection β values as well as decision-bound modeling results. Because these disruptions to implicit learning attenuate the base-rate effect, we conclude that implicit learning does indeed underlie the influence of base-rates learned through direct experience. This suggests that the implicit learning system postulated by the COVIS theory of categorization (Ashby, Alfonso-Reese, Turken, & Waldron Psychological Review, 105, 442-481, 1998) may be involved in developing sensitivity to category base-rates.

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Year:  2015        PMID: 25037267      PMCID: PMC4946800          DOI: 10.3758/s13423-014-0694-2

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  15 in total

1.  Category discriminability, base-rate, and payoff effects in perceptual categorization.

Authors:  C J Bohil; W T Maddox
Journal:  Percept Psychophys       Date:  2001-02

2.  On the generality of optimal versus objective classifier feedback effects on decision criterion learning in perceptual categorization.

Authors:  Corey J Bohil; W Todd Maddox
Journal:  Mem Cognit       Date:  2003-03

3.  Procedural learning in perceptual categorization.

Authors:  F Gregory Ashby; Shawn W Ell; Elliott M Waldron
Journal:  Mem Cognit       Date:  2003-10

Review 4.  Toward a unified theory of decision criterion learning in perceptual categorization.

Authors:  W Todd Maddox
Journal:  J Exp Anal Behav       Date:  2002-11       Impact factor: 2.468

5.  Delayed feedback effects on rule-based and information-integration category learning.

Authors:  W Todd Maddox; F Gregory Ashby; Corey J Bohil
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2003-07       Impact factor: 3.051

6.  Observational versus feedback training in rule-based and information-integration category learning.

Authors:  F Gregory Ashby; W Todd Maddox; Corey J Bohil
Journal:  Mem Cognit       Date:  2002-07

7.  AIC model selection using Akaike weights.

Authors:  Eric-Jan Wagenmakers; Simon Farrell
Journal:  Psychon Bull Rev       Date:  2004-02

Review 8.  Human category learning 2.0.

Authors:  F Gregory Ashby; W Todd Maddox
Journal:  Ann N Y Acad Sci       Date:  2010-12-23       Impact factor: 5.691

9.  Dual-task interference in perceptual category learning.

Authors:  Dagmar Zeithamova; W Todd Maddox
Journal:  Mem Cognit       Date:  2006-03

10.  A neuropsychological theory of multiple systems in category learning.

Authors:  F G Ashby; L A Alfonso-Reese; A U Turken; E M Waldron
Journal:  Psychol Rev       Date:  1998-07       Impact factor: 8.934

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  3 in total

1.  Base-rate sensitivity through implicit learning.

Authors:  Andrew J Wismer; Corey J Bohil
Journal:  PLoS One       Date:  2017-06-20       Impact factor: 3.240

2.  Human online adaptation to changes in prior probability.

Authors:  Elyse H Norton; Luigi Acerbi; Wei Ji Ma; Michael S Landy
Journal:  PLoS Comput Biol       Date:  2019-07-08       Impact factor: 4.475

3.  Feature-Based Attentional Weighting and Re-weighting in the Absence of Visual Awareness.

Authors:  Lasse Güldener; Antonia Jüllig; David Soto; Stefan Pollmann
Journal:  Front Hum Neurosci       Date:  2021-01-29       Impact factor: 3.169

  3 in total

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